predict_g2p_bert.py报错 about g2pw HOT 1 OPEN

def predict(model, dataloader, device, labels, turnoff_tqdm=False):
    model.eval()
    all_preds = []
    all_confidences = []
    with torch.no_grad():
        generator = dataloader if turnoff_tqdm else tqdm(dataloader, desc='predict')
        for data in generator:
            input_ids, token_type_ids, attention_mask, phoneme_mask, char_ids, position_ids = \
                [data[name].to(device) for name in ('input_ids', 'token_type_ids', 'attention_mask', 'phoneme_mask', 'char_ids', 'position_ids')]
            probs = model(
                input_ids=input_ids,
                token_type_ids=token_type_ids,
                attention_mask=attention_mask,
                phoneme_mask=phoneme_mask,
                char_ids=char_ids,
                position_ids=position_ids
            )
            max_probs, preds = map(lambda x: x.cpu().tolist(), probs.max(dim=-1))
            all_preds += [labels[pred] for pred in preds]
            all_confidences += max_probs
    return all_preds, all_confidences